Zobrazeno 1 - 10
of 18 804
pro vyhledávání: '"Bakr, A. A."'
Autor:
Bakr, Mustafa, Fasciati, Simone D., Cao, Shuxiang, Campanaro, Giulio, Wills, James, Alghadeer, Mohammed, Piscitelli, Michele, Shteynas, Boris, Chidambaram, Vivek, Leek, Peter J.
Hardware efficient methods for high fidelity quantum state measurements are crucial for superconducting qubit experiments, as qubit numbers grow and feedback and state reset begin to be employed for quantum error correction. We present a 3D re-entran
Externí odkaz:
http://arxiv.org/abs/2412.14853
Autor:
Cao, Shuxiang, Zhang, Zijian, Alghadeer, Mohammed, Fasciati, Simone D, Piscitelli, Michele, Bakr, Mustafa, Leek, Peter, Aspuru-Guzik, Alán
Fully automated self-driving laboratories are promising to enable high-throughput and large-scale scientific discovery by reducing repetitive labour. However, effective automation requires deep integration of laboratory knowledge, which is often unst
Externí odkaz:
http://arxiv.org/abs/2412.07978
Autor:
Bakr, Mustafa
Scaling superconducting quantum processors to large qubit counts faces challenges in control signal delivery, thermal management, and hardware complexity, particularly in achieving microwave signal multiplexing and long-distance quantum information r
Externí odkaz:
http://arxiv.org/abs/2411.01345
We introduce the idea of AquaFuse, a physics-based method for synthesizing waterbody properties in underwater imagery. We formulate a closed-form solution for waterbody fusion that facilitates realistic data augmentation and geometrically consistent
Externí odkaz:
http://arxiv.org/abs/2411.01119
Autor:
Elshaarawy, Mohamed, Saeed, Ashrakat, Sheta, Mariam, Said, Abdelrahman, Bakr, Asem, Bahaa, Omar, Gomaa, Walid
This paper proposes a machine learning approach for classifying classical and new Egyptian music by composer and generating new similar music. The proposed system utilizes a convolutional neural network (CNN) for classification and a CNN autoencoder
Externí odkaz:
http://arxiv.org/abs/2410.19719
Autor:
Fasciati, Simone D., Shteynas, Boris, Campanaro, Giulio, Bakr, Mustafa, Cao, Shuxiang, Chidambaram, Vivek, Wills, James, Leek, Peter J.
We realize a single-Josephson-junction transmon qubit shunted by a simple geometric inductor. We couple it capacitively to a conventional transmon and show that the ZZ interaction between the two qubits is completely suppressed when they are flux-bia
Externí odkaz:
http://arxiv.org/abs/2410.10416
The rapid expansion of video content across a variety of industries, including social media, education, entertainment, and surveillance, has made video summarization an essential field of study. The current work is a survey that explores the various
Externí odkaz:
http://arxiv.org/abs/2410.04449
Autor:
Hussein, Ahmed, Elsetohy, Alaa, Hadhoud, Sama, Bakr, Tameem, Rohaim, Yasser, AlKhamissi, Badr
Designing expressive typography that visually conveys a word's meaning while maintaining readability is a complex task, known as semantic typography. It involves selecting an idea, choosing an appropriate font, and balancing creativity with legibilit
Externí odkaz:
http://arxiv.org/abs/2410.03748
The rise of short-form videos on platforms like TikTok has brought new challenges in safeguarding young viewers from inappropriate content. Traditional moderation methods often fall short in handling the vast and rapidly changing landscape of user-ge
Externí odkaz:
http://arxiv.org/abs/2410.00403
Autor:
Felemban, Abdulwahab, Bakr, Eslam Mohamed, Shen, Xiaoqian, Ding, Jian, Mohamed, Abduallah, Elhoseiny, Mohamed
We introduce iMotion-LLM: a Multimodal Large Language Models (LLMs) with trajectory prediction, tailored to guide interactive multi-agent scenarios. Different from conventional motion prediction approaches, iMotion-LLM capitalizes on textual instruct
Externí odkaz:
http://arxiv.org/abs/2406.06211